An engineer designed a valve that will regulate water pressure on an automobile engine. The engineer designed the valve such tha
1 answer:
The p-value from the hypothesis test is 0.142 i.e., greater than the given significance level of 0.05. So, the null hypothesis is not rejected. The z-score for the given sample is 1.471.
<h3>What is the decision rule for the p-value approach to hypothesis testing?</h3>The decision rule based on p-value states,
- If p > α (significance level), then the null hypothesis is not rejected
- If p < α (significance level), then the null hypothesis is rejected in favor of the alternative hypothesis.
Since it is given that the valve would produce a mean pressure of 5.4 pounds/square inch. I.e., μ = 5.4 p/si
So, Defining the hypothesis:
Null hypothesis H0: μ = 5.4
Alternative hypothesis Ha: μ ≠ 5.4
It is given that,
The valve was tested on 24 engines. I.e., Sample size n = 24
The sample mean X = 5.7
Standard deviation σ = 1.0 and
The significance level = 0.05
Since the population distribution is approximately normal,
the test statistic is calculated as follows:
z = (X - μ)/(σ/)
On substituting the value,
z = (5.7 - 5.4)/(1.0/)
= (0.3)/0.204
= 1.471
Fron this z-score, the p-value is calculated as 0.142.
Since, the value of p > 0.05 (significance level), the null hypothesis is not rejected.
Learn more about hypothesis testing here:
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a) The 90% confidence interval of the percentage of all mangoes on the truck that fail to meet the standards is: (7.55%, 12.45%).
b) The margin of error is: 2.45%.
c) The 90% confidence is the level of confidence that the true population percentage is in the interval.
d) The needed sample size is: 271.
<h3>What is a confidence interval of proportions?</h3>A confidence interval of proportions has the bounds given by the rule presented as follows:
The margin of error is given by:
The variables are listed as follows:
is the sample proportion, which is also the estimate of the parameter.
- z is the critical value.
- n is the sample size.
The confidence level is of 90%, hence the critical value z is the value of Z that has a p-value of , so the critical value is z = 1.645.
The sample size and the estimate are given as follows:
The margin of error is of:
The interval is given by the estimate plus/minus the margin of error, hence:
- The lower bound is: 10 - 2.45 = 7.55%.
- The upper bound is: 10 + 2.45 = 12.45%.
For a margin of error of 3% = 0.03, the needed sample size is obtained as follows:
n = 271 (rounded up).
More can be learned about the z-distribution at brainly.com/question/25890103
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